Machine learning can be used for several different software data analytics tasks, providing useful insights into software processes and products.
Map-Reduce-based runtime environments provide good performance on cloud architectures above all on data analytics tasks working on large data collections.
For many modern big data applications, the complexity of analytic tasks often require the combination of NoSQL databases and Hadoop.
Identical to the data analytic strategy employed in the only known cued task switching studies of ADHD samples, [ 57, 58], task switching data were subjected to two separate sets of repeated-measures ANOVAs which respectively tested group differences in switch costs (i.e. switch – repetition trials in MBs) and mixing costs (i.e. MB repetition trials – PRB trials).
Novelty detection is an interesting research topic in many data analytics and machine learning tasks ranging from video security surveillance, network abnormality detection, and detection of abnormal gene expression sequence to name a few.
In the recent era, determining the best strategy for data analytics is an important task to an organization.
Future work includes extending the framework to deal with large-scale data sets, to incorporate novel data analytics techniques specifically defined for tasks such as user sentiment analysis and to incorporate novel IoT technologies.
In performing discriminative tasks in Big Data Analytics one can use Deep Learning algorithms to extract complicated nonlinear features from the raw data, and then use simple linear models to perform discriminative tasks using the extracted features as input.
Either by design or by physical limitations, a large number of measurements never reach the central processing stations, making the task of data analytics even more problematic.
Through perusing [110], we can know that, on the one hand, the seminal works on SA, such as by Robbins Monro and Widrow algorithms, and the workhorse behind several classical SP tools, such as LMS and RLS algorithms, carried rich potential in modern learning tasks for big data analytics.
